Optimal Operation of Autonomous Energy System Based on Multi-objective Approach

This research aims to explore the scheduling strategies for an autonomous energy system (AES), with multi-objectives modeling.It has been proposed that implementing demand management can enhance both technical and economic performance during operations.This study aims to reduce operational expenses and improve voltage metrics by employing a load optimization strategy.The Particle Swarm Optimization (PSO) algorithm is utilized to address the problem of optimizing complex functions and finding optimal solutions in various fields, including engineering, computer science, and economics.The ideal optimal solution, found among the non-dominated solutions, is achieved through the fuzzy method.Case studies are conducted on the 33 bus test system to evaluate the effectiveness of the proposed strategy.By implementing demand management, operational costs are reduced by 6.12%, while voltage indices show an improvement of 9.65% compared to the absence of demand management practices.